Instructions to use lylosn/plum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lylosn/plum with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/InstantID", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lylosn/plum") prompt = "plum" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 332 Bytes
1e38a9c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ---
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: plum
output:
url: images/profile_plum (17).png
base_model: InstantX/InstantID
instance_prompt: null
---
# plum
<Gallery />
## Download model
[Download](/lylosn/plum/tree/main) them in the Files & versions tab.
|